Hillert Materials Modeling Colloquium series V: Accelerated Experimentation and Holistic Integration with Computational Data for Accelerated Materials Design
In this session Professor Ji-Cheng Zhao from the University of Maryland will describe experimental techniques for rapid collections of materials data and holistic approaches to integrate experimental and computational data. Zhao holds 49 issued U.S. patents and was the 2001 winner of the prestigious Hull Award from GE.
Time: Tue 2022-08-30 15.00
Lecturer: Professor Ji-Cheng ‘JC’ Zhao
Experimental techniques for rapid collections of materials data and holistic approaches to integrate experimental and computational data will be described with examples. Localized property measurements on composition gradients created in diffusion multiples allow high-throughput collection of several materials properties as a function of composition, in addition to phase diagrams and diffusion coefficients.
A novel approach was developed to rapidly establish reliable diffusion coefficient (atomic mobility) databases by holistically integrating both experimental and computed data. Dual-anneal diffusion multiples allow rapid and systematic collection of big datasets of phase precipitation kinetics and morphological evolution across wide ranges of compositions as a function of time and temperature. An approach that iteratively and holistically integrate experimental results with model predictions can be the most effective in both establishing materials databases and understanding of various mechanisms.
Hillert Materials Modeling Colloquium Series is arranged by Hillert Modeling Laboratory
Department of Materials Science and Engineering
KTH Royal Institute of Technology